[R] Interpreting a Logit regression result

Mohamed Farah m.farah at sc.qa
Fri Feb 6 18:02:48 CET 2015


Dear Michael,

Thank you for your comment. My difficulty is concerned with the high coefficient of the independent variable. The result I get fro running a logit regression is:
ylog e^x= -3.3499+ X4.4738. Changing the numbers to exponents of e (antilog) to better interpret the results, I get  y = 0.035087863 + 87.68931008 x.

Mohamed

________________________________________
From: Michael Dewey [info at aghmed.fsnet.co.uk]
Sent: Friday, February 06, 2015 6:58 PM
To: Mohamed Farah; r-help at r-project.org
Subject: Re: [R] Interpreting a Logit regression result

Dear Mohamed

Your dataset did not make it through, the list strips most attachments.

In my area of application I would be suspicious that such an odds ratio
was the result of a data error or my misunderstanding of the underlying
science. You are probably in the best position to judge both of these in
your area.

Michael


On 06/02/2015 07:42, Mohamed Farah wrote:
> I have run a logit regression with two categorical variables (with 0 and 1)  as the values. i.e. payment (1) / non-payment(0) on profit (profitable =1, non-profitable=0) on 375 entities. Here is the result from R:
>
>
>
>> divgress <-glm(Div~PRFD, family=binomial(link="logit"), data=divs)
>> summary(divgress)
>
> Call:
> glm(formula = Div ~ PRFD, family = binomial(link = "logit"),
>      data = divs)
>
> Deviance Residuals:
>      Min       1Q   Median       3Q      Max
> -1.6765  -0.2626   0.7502   0.7502   2.6017
>
> Coefficients:
>              Estimate Std. Error z value Pr(>|z|)
> (Intercept)  -3.3499     0.7194  -4.656 3.22e-06 ***
> PRFD          4.4738     0.7311   6.119 9.41e-10 ***
> ---
> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>
> (Dispersion parameter for binomial family taken to be 1)
>
>      Null deviance: 491.84  on 376  degrees of freedom
> Residual deviance: 371.78  on 375  degrees of freedom
> AIC: 375.78
>
> Number of Fisher Scoring iterations: 6
>
>
>
> My question is that the coefficient of the independent variable (log-odds) at 4.4738  is difficult to interpret. I have obtained the exponent of the coefficient below and as the result of 87.69..   shown below shows, the number is high which makes suspicious that there is something not working right.
>
>
>
>> exp(coef(divgress))
> (Intercept)        PRFD
>   0.03508772 87.69230769
>>
>
>
>
> The dataset is attached. I appreciate your help.
>
>
>
>
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--
Michael
http://www.dewey.myzen.co.uk

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Please note that none of the Supreme Committee for Delivery and Legacy or any of its affiliated entities will have any liability for any incorrect or incomplete transmission of the information contained in this email nor for any delay in its receipt. Emails are not secure and cannot be guaranteed to be error free. Anyone who communicates with us by email is taken to accept these risks. Any views or opinions expressed in this email are solely those of the author and do not necessarily represent those of the Supreme Committee for Delivery and Legacy or any of its affiliated entities. Any logo trademark or other intellectual property forming part of or attached to this email belongs exclusively to the Supreme Committee for Delivery and Legacy. Any unauthorised reproduction copying or other use by you or others is strictly prohibited.



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